Collaborative Research: CyberTraining: Pilot: Cybertraining to Develop FAIR Data Competencies for Bioengineering Students

Data-driven methods have a significant role in advancing bioengineering research. The bioengineering cyber training program equips future researchers and practitioners with data-driven methods that can be applied to a wide-range of engineering problems. The program supports data-driven bioengineering education, fosters inclusivity, and benefits society through the training of undergraduate bioengineering students and the generation and release of training material and hands-on project data. The program ensures accessibility to a wide audience and promotes diversity in STEM fields. It advances data-driven bioengineering education by emphasizing team building, FAIR (Findable, Accessible, Interoperable, and Reusable) data principles, and real-world projects. The program provides a comprehensive curriculum covering data science concepts, workflows, visualizations, FAIR data principles, and analytics, with a specific focus on applying these principles in the field of bioengineering. The program includes a boot camp, a 10-week hands-on training program, and a research symposium with a poster competition. The program emphasizes team building, outreach to underrepresented groups, and collaboration with industry partners to empower students and enable them to work on real-world data-driven bioengineering projects. The 10-week training program includes three components: an instructional component that covers the principles of data-driven bioengineering, a hands-on guided project component that complements the instruction part, and a team-based project component. The team-based project component matches student groups with partners from industry and academia to allow students the opportunity to work on real data-driven bioengineering problems. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.